This research aims to understand the role of fandom in driving the growth of the fanworks market in Indonesia, specifically through the case study of Comifuro, a popular cultural event that is the center for the distribution of fan-made works. The research method used is qualitative, with a self-report approach from participants who are directly involved as creators and consumers at Comifuro since the beginning of its implementation. The results of the study show that the emotional connection between fans and copyrighted works encourages active involvement in producing and consuming fanworks. Fanworks are not only a forum for expression, but also a means of creative monetization that is socially legal even though it is legally gray. Comifuro gives creators a space for freedom of expression, bringing them together directly with audiences in an inclusive and supportive space. The surge in visitors and participants since the post-pandemic reflects the high demand for fandom content, as well as demonstrating the power of communities in supporting the creative economy. This research emphasizes the importance of recognizing the role of fans as the main motor in popular culture dynamics and community-based digital economy.
 

Nowadays, the construction, monitoring, quality control, and maintenance of roads always require high-precision, easy-to-use measuring devices in the field. This study develops an embedded computer program using the YOLOv8 model integrated into a smart road length measuring device to detect road surface cracks. First, the study analyzes and clarifies the outstanding points of the YOLOv8 model, including anchor-free: Eliminates the use of traditional anchor boxes, helping to simplify the training process, increase accuracy and reduce computational costs; C2f (Cross-Stage Partial with feature fusion); Replacing CSSPLayer in YOLOv5, this module improves feature extraction and maintains good computational performance; SPFF (Spatial Pyramid Pooling - Fast): Helps expand the receptive field without increasing computational costs, supporting object recognition at multiple scales; PAN++: Enhances the transfer of features from lower layers to the output, helping to detect small objects such as cracks well. Then, this work evaluated the performance of the proposed model by applying YOLOv8 on the surface crack dataset taken from the open-source Roboflow Universe. The results showed that the developed YOLOv8 model achieved good results with the recall indexes of 57.3%, mAP50 59.3%, precision of 64.4% mAP50-95 48.9% for YOLOv8n model, and can improve the accuracy further, reaching 79.8% using the YOLOv8m model, while still meeting the real-time processing speed of the device. These experimental results using the YOLOv8 model for detecting cracks on DongAnh road, Hanoi, Vietnam, confirm the possibility of applying the integrated road crack detection model on smart road length measuring devices in practice, achieved a precision of 43.3%, supporting the survey, inspection, supervision, construction and management of traffic infrastructure more scientifically and effectively

The integration of Artificial Intelligence (AI) into scientific advancements has become a crucial part of daily life for many people. In the creative industry, AI has the potential to not only enhance the level of creativity, but also productivity. The legal implications of this development must be carefully analyzed for the development of the creative industry, to establish a legal position on where AI stands in the increasingly competitive market, especially when Intellectual Property Right (IPR) as a key factor is taken into account. This research examines the need for a legal framework for AI. It was conducted through the lens of intellectual property law, to determine its place within existing IPR regimes using the comparative legal method. The results conceptually justify the urgency to regulate AI, and highlights the taxonomy dilemma of AI-generated works within the current dynamics of the creative industry, indicating a taxonomy dilemma. Further analysis also indicates that while there’s a decent urgency to address all of the normative issues that exist within Indonesia’s IPR legal framework, it’s imperative that Indonesia prioritizes the development of the copyright and patent regimes, which are closely related to the nature of AI-generated works.

Purpose: Breast cancer remains a significant cause of mortality among women, requiring accurate diagnostic methods. Traditional classification models often face accuracy challenges due to missing values and irrelevant features. This investigation advances the classification of breast cancer through the amalgamation of the C4.5 algorithm with K-Nearest Neighbor (KNN) imputation and Relief feature selection methodologies, thereby augmenting data integrity and enhancing classification efficacy.
Methods: The Wisconsin Breast Cancer Database (WBCD) was the core reference for evaluating the proposed methodology. KNN imputation addressed missing values, while Relief selected the most relevant features. The C4.5 algorithm executed training by utilizing data segregations in the corresponding proportions of 70:30, 80:20, and 90:10, with its efficiency gauged through a range of metrics, particularly accuracy, precision, recall, and F1-score.
Result: This innovative methodology achieved the highest classification accuracy of 98.57%, surpassing several existing models. Particularly noteworthy, the strategy being analyzed exhibited remarkable success relative to PSO-C4.5 (96.49%), EBL-RBFNN (98.40%), Gaussian Naïve Bayes (97.50%), and t-SNE (98.20%), demonstrating associated advancements of 2.08%, 0.17%, 1.07%, and 0.37%. These results confirm its effectiveness in handling missing values and selecting relevant features.
Novelty: Unlike prior studies that addressed missing values and feature selection separately, this research integrates both techniques, enhancing classification accuracy and computational efficiency. The findings suggest that this approach provides a reliable breast cancer diagnosis method. Future work could explore deep learning integration and validation on larger datasets to improve generalizability.

Appropriated artwork refers to the practice of using pre-existing objects or images into new works of art with little or no significant changes to the original form. This trend developed into the Pop Art movement, where one of the characteristic features was the use of images from mass media, as seen in the works of Andy Warhol, including the transformation of Campbell's soup cans into iconic works of art. Although widely appreciated, this work has drawn criticism regarding copyright infringement, raising the question: where do one artist's rights draw on another? To what extent is the appropriation of copyright protected works considered legal without violating the rights of the original creator?
The research results show that the two legal systems differ significantly in the aspects of exclusive rights, moral rights, protected works, exceptions, and duration of protection. The challenge in understanding fair use lies in determining the boundaries between the rights of one artist and another. The fair use doctrine assesses four main factors: the purpose and character of the use, the nature of the original work, the proportion of the work used, and the impact on the market. Courts in the US often favor fair use if elements of transformation are identified, measuring the extent to which the appropriated work carries elements of originality or new creativity. Indonesia could consider adopting the fair use doctrine by adapting the concept through ministerial regulations or other implementing regulations.

This study aims to develop the Electronic Record Information System for Education (ERISE) as a learning medium to accommodate practical learning of digital archive management at VHS OMBS. The research employed a Research and Development (R&D) method using the Richey & Klein model, consisting of three phases: design, development, and evaluation. The respondents in this study were 14 individuals, comprising seven teachers, five archival practitioners, and two media experts. Data were collected using questionnaires, focus group discussions (FGDs), and interviews, with instruments including a 5-point Likert-scale questionnaire, FGD guidelines, and interview protocols. Data were analyzed descriptively, with raw scores converted to a 5-point scale and the minimum media feasibility category set at a “B” rating. The results indicate that (1) the ERISE application has been developed as a web-based learning system for digital archive management practice by the needs analysis, design, and development stages; and (2) the feasibility test yielded an average score in the “Very Good” (“A”) category. This learning medium is expected to make a concrete contribution to enriching vocational practice, particularly by facilitating the entire archiving process starting from receipt, recording, distribution, classification, retention, and digital signatures.

Nowadays, universities use social networks as a crucial tool for providing information and engaging students. Factors like openness, perceived interaction, and parasocial interaction influence students' feelings toward these interactions. Parasocial interaction, the imagined relationship between the sender and receiver, significantly impacts students' attitudes and engagement. This study aims to evaluate the effects of perceived interaction, openness, and parasocial interaction on student satisfaction with university social networks. A survey of 346 students from universities in Hanoi, Vietnam, was conducted, and data were analyzed by the structural equation model (SEM). Results show that perceived interaction, openness, and parasocial interaction positively impact student satisfaction. Moreover, parasocial interaction mediates the relationship between perceived interaction, openness, and satisfaction. Additionally, content quality and responsiveness on social networks play a vital role in shaping students' perceptions and engagement. Universities that provide high-quality, timely content and meaningful interactions can strengthen student trust and satisfaction. These findings suggest that universities should optimize their social media strategies, focusing on interactive communication and content relevance to enhance student relationships and engagement.

This research examines how economic literacy and digital literacy influence economic teacher readiness through self-efficacy as a mediating variable among Economic Education students from the State University of Surabaya. Using an explanatory research type and a quantitative approach, this study employs PLS-SEM methodology. The investigation gathered questionnaire responses from 106 participants, using the proportionate stratified random sampling technique. First, the result of this study stated that economic literacy does not significantly influence economic teacher readiness. Second, digital literacy and self-efficacy positively influence economic teacher readiness. Third, economic literacy and digital literacy also have a positive influence on self-efficacy. Last, while self-efficacy did not mediate the influence of economic literacy, it did mediate the influence of digital literacy on economic teacher readiness. These results suggest the necessity for alternative comprehensive approaches to improve economic literacy towards economic teacher readiness, other than through self-efficacy. Therefore, educational institutions should enhance digital literacy and self-efficacy to boost economic teacher readiness.

The number of pesantren in Indonesia is vast and has contributed to economic development and growth. The development of pesantren today is about providing entrepreneurial provisions for students (santri) so that they will be ready to enter the community by having the ability to act creatively and innovatively. This research intends to strengthen students' social entrepreneurship intentions by applying motivational training based on developing self-potential. The research to be carried out is experimental research with quasi-experimental research techniques (quasi-experimental design). The research was conducted at the Pondok Pesantren as Salafy Al Asror, Semarang City, Central Java, Indonesia. The data collection techniques used are tests, observations, and interviews. The results indicated that managerial ability, motivational ability, creativity, and communication significantly affect the intention of the student to pursue social entrepreneurship. This research also develops an entrepreneurial model for students by utilizing the abilities possessed by students, namely managerial abilities, motivation, creativity, and communication. The model developed was tested differently and, based on the model developed, was effective in increasing the intention of students to pursue social entrepreneurship. Thus, this research has contributed to creating social enterprise intentions in students through the students' self-potential.

This study seeks to examine the factors influencing the financial management accountability of Pondok Pesantren, with a particular emphasis on the pivotal role of Kiai leadership. By using structural equation modeling (SEM), this paper focuses on several key variables, namely Kiai leadership, human resource (HR) competency, perception of accounting standards, and information technology (IT) usage. The research was carried out at a Salafiyah Pondok Pesantren, involving students, asatidz councils, and administrators as respondents. Data was collected from 140 respondents using purposive sampling. Data was collected through a questionnaire and analyzed using SEM to examine both direct relationships and indirect (mediated) effects among the study variables. The findings of the study suggest that the leadership of the Kiai and the competency of human resources play a vital role in shaping Pesantren's financial accountability. In contrast, the adoption of information technology and the perception of accounting standards do not significantly impact. Furthermore, Kiai leadership strongly influences HR competency, IT usage, and perceptions of accounting guidelines. The study also reveals that HR competency significantly mediates Kiai leadership and financial accountability. These results emphasize the strategic importance of strengthening HR capabilities and reaffirm Kiai leadership's central role in enhancing financial management practices' accountability in Pesantren.